scholarly journals Using Domain Knowledge to Boost Case-Based Diagnosis: An Experimental Study in a Domain with Very Poor Data Quality

2004 ◽  
pp. 137-151
Author(s):  
Lu Zhang ◽  
Frans Coenen ◽  
Paul Leng
Keyword(s):  
Experimental Study ◽  
Data Quality ◽  
Domain Knowledge ◽  
Case Based

Applying Domain Knowledge for Data Quality Assessment in Dermatology

2017 ◽  
pp. 147-156
Author(s):  
Nemanja Igić ◽  
Branko Terzić ◽  
Milan Matić ◽  
Vladimir Ivančević ◽  
Ivan Luković
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Domain Knowledge ◽  
Data Quality Assessment

scholarly journals Case-based knowledge formalization and reasoning method for digital terrain analysis – application to extracting drainage networks

2016 ◽  
Vol 20 (8) ◽  
pp. 3379-3392 ◽  
Author(s):  
Cheng-Zhi Qin ◽  
Xue-Wei Wu ◽  
Jing-Chao Jiang ◽  
A-Xing Zhu
Keyword(s):  
Domain Knowledge ◽  
Case Based Reasoning ◽  
Preliminary Evaluation ◽  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Digital Terrain ◽  
Drainage Networks ◽  
Building Process ◽  
Context Knowledge ◽  
Case Based

Abstract. Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context (including the target task, the terrain in the study area, the DEM resolution, etc.), which is referred to as application-context knowledge. However, existing DTA-assisted tools often cannot use application-context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This situation makes the DTA workflow-building process difficult for users, especially non-expert users. This paper proposes a case-based formalization for DTA application-context knowledge and a corresponding case-based reasoning method. A case in this context consists of a series of indices that formalize the DTA application-context knowledge and the corresponding similarity calculation methods for case-based reasoning. A preliminary experiment to determine the catchment area threshold for extracting drainage networks has been conducted to evaluate the performance of the proposed method. In the experiment, 124 cases of drainage network extraction (50 for evaluation and 74 for reasoning) were prepared from peer-reviewed journal articles. Preliminary evaluation shows that the proposed case-based method is a suitable way to use DTA application-context knowledge to achieve a marked reduction in the modeling burden for users.

Domain knowledge and data quality perceptions in genome curation work

2015 ◽  
Vol 71 (1) ◽  
pp. 116-142 ◽  
Author(s):  
Hong Huang
Keyword(s):  
Data Quality ◽  
Domain Knowledge ◽  
Design Methodology ◽  
Quality Criteria ◽  
Computational Science ◽  
Survey Method ◽  
New Approach ◽  
Content Type ◽  
Genome Data ◽  
Quality Perceptions

Purpose – The purpose of this paper is to understand genomics scientists’ perceptions in data quality assurances based on their domain knowledge. Design/methodology/approach – The study used a survey method to collect responses from 149 genomics scientists grouped by domain knowledge. They ranked the top-five quality criteria based on hypothetical curation scenarios. The results were compared using χ2 test. Findings – Scientists with domain knowledge of biology, bioinformatics, and computational science did not reach a consensus in ranking data quality criteria. Findings showed that biologists cared more about curated data that can be concise and traceable. They were also concerned about skills dealing with information overloading. Computational scientists on the other hand value making curation understandable. They paid more attention to the specific skills for data wrangling. Originality/value – This study takes a new approach in comparing the data quality perceptions for scientists across different domains of knowledge. Few studies have been able to synthesize models to interpret data quality perception across domains. The findings may help develop data quality assurance policies, training seminars, and maximize the efficiency of genome data management.

Extracting information from free-text aircraft repair notes

2001 ◽  
Vol 15 (4) ◽  
pp. 295-305 ◽  
Author(s):  
BENOIT FARLEY
Keyword(s):  
Decision Support ◽  
Domain Knowledge ◽  
Electronic Version ◽  
Free Text ◽  
Case Based Reasoning ◽  
Lexical Information ◽  
Text Format ◽  
Support Methods ◽  
Case Based ◽  
Information Extraction System

For every problem mentioned by crew members in an aircraft log book, an associated repair action note is entered in the same log book by a maintenance technician after the problem has been handled. These hand-written repair notes, subsequently transcribed into a database, give an account of the actions undertaken by the technicians to fix the problems. Written in a free-text format with peculiar linguistic characteristics, including many arbitrary abbreviations and missing auxiliaries, they contain valuable information that can be used for decision support methods such as case-based reasoning. We use natural language techniques in our information extraction system to analyze the structure and contents of these notes in order to determine the pieces of equipment involved in a repair and what was done to them. Lexical information and domain knowledge are extracted from an electronic version of the illustrated parts catalog for the particular airplane, and are used at different stages of the process, from the morpholexical analysis to the evaluation of the semantic expression generated by the syntactical analyzer.

scholarly journals Case-based formalization and reasoning method for knowledge in digital terrain analysis – Illustrated by determining the catchment area threshold for extracting drainage networks

2016 ◽  
Author(s):  
C.-Z. Qin ◽  
X.-W. Wu ◽  
J.-C. Jiang ◽  
A.-X. Zhu
Keyword(s):  
Catchment Area ◽  
Domain Knowledge ◽  
Case Based Reasoning ◽  
Preliminary Evaluation ◽  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Digital Terrain ◽  
Drainage Networks ◽  
Context Knowledge ◽  
Case Based

Abstract. Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context (including the target task, the terrain in the study area, the DEM resolution, etc.), which is referred to as application-context knowledge. However, existing DTA-assisted tools often cannot use application-context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This situation makes the DTA workflow-building process difficult for users, especially non-expert users. This paper proposes a case-based formalization for DTA application-context knowledge and a corresponding case-based reasoning method. A case in this context consists of a series of indices that formalize the DTA application-context knowledge and the corresponding similarity calculation methods for case-based reasoning. A preliminary experiment to determine the catchment area threshold for extracting drainage networks has been conducted to evaluate the performance of the proposed method. In the experiment, 124 cases of drainage network extraction (50 for evaluation and 74 for reasoning) were prepared from peer-reviewed journal articles. Preliminary evaluation results show that the proposed case-based method is a suitable way to use DTA application-context knowledge to achieve a marked reduction in the modeling burden for users.

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